Sustainable and scalable data management services with skilled resources are paramount to meet your clinical trial and research goals.
Health systems, oncology centers, academic researchers, and others must curate and standardize clinical trial data to conduct meaningful analysis. This labor-intensive process is mission critical to accelerate research and improve diagnosis and treatment. Yet the increasing volume of clinical trials and data, industrywide staffing shortages, and evolving regulatory requirements are hindering the curation of high-quality data and overwhelming already burdened clinicians and researchers.
Sustainable, scalable data management services with skilled resources are essential to ensure high-quality data curation for academic research. As the pressure to process data faster and more inexpensively increases, clinical trial leaders are turning to outsourcing partnerships to meet deadlines and to reduce the time from data abstraction and hypothesis to publication and treatment. Below are four reasons why outsourcing can be a strategic method to meet clinical trial data management goals.
1. The increasing volume of RWD is overwhelming to manage.
The number of clinical trials and their resulting data are increasing. More than 10,000 clinical trials started in 2021 and 2022, and there were over 16,000 clinical trials active in 2022. The duration of phase 3 clinical trials nearly doubled in the last decade, increasing from two years in 2010 to 3.5 years in 2022.[i]
Real-world data (RWD) is scattered across multiple systems. Typically, healthcare data is maintained in multiple disparate systems—structured data and unstructured patient data in EHRs, claims and billing systems, registries, and more. Clinical trial data includes data in clinical trial management systems (CTMS) and data sets maintained in personal spreadsheets and databases.
In a survey of professionals involved in clinical data management, 50% of respondents reported using up to five different data sources, and 37% use between six and 10.[ii] CTMS and EHR platforms can yield rich data sets but are often siloed. The increasing number of trials, siloed data sources, data backlogs, and other factors are driving the need to determine the best way to manage, harmonize, and democratize clinical trial data.
2. Staffing shortages of skilled resources continues to be a challenge.
For the first time in nearly two decades, staffing shortages have replaced financial challenges as a top concern among CEOs. The U.S. labor demand in life sciences services remains high coming out of the pandemic.[iii] Turnover is prevalent, and researchers are stretched. They are also high-paid resources that should be focused on research rather than curating data.
Research organizations are exploring options to meet the growing demands of registry data policies, procedures, reporting analysis, and data submission that call for knowledgeable workers. This also opens the door to leverage natural language processing (NLP) and AI for improved efficiencies and productivity,[iv] but these technologies also require a highly skilled and specialized workforce.
3. Clinical trial data management is labor intensive.
In a survey of top clinical data management professionals, 95% of respondents reported that manual effort is involved in aggregating, cleaning, and transforming clinical trial data, and two out of three respondents experienced issues with the process.[v]
In that same survey:
- 81% of respondents indicated data governance issues as the biggest challenge with clinical trial data in meeting regulatory compliance.
- More than half (58%) indicated a lack confidence in quality or completeness of their data from an audit and compliance perspective.
- When asked about the top operational challenges with clinical trial data, data completeness (51%), quality (45%), and cleaning (43%) were the top three concerns.[vi]
Clinically relevant data is often difficult to capture because it’s buried in unstructured content such as physician notes and diagnostic reports. Plus, the increasing complexity of trial and data management results in a higher risk of noncompliance. Improving data management and data governance in clinical research is critical to ensure high-quality clinical trial outcomes and RWD curation.
4. Evolving industry regulations require strong oversight.
Clinical trial sponsors are having to adopt more effective methods for clinical trial oversight in relation to metrics, deliverables, and quality—in part, due to new regulatory requirements such as the 21st Century Cures Act (Cures Act). The Cures Act aims to increase innovation, development, and review of new medical products by modernizing clinical trial designs. As part of the act, the FDA references the use of real-world evidence (RWE), including a new framework for use of RWD and RWE in effective decision making.
Updates to FDA guidelines for clinical research best practices also point to the need to step up data management and curation. For example, the FDA ICH GCP E6 R2 guidance includes two relevant items: (1) requirements for centralized storage and access control of all regulatory and source documents, and (2) an “always on” audit trail that tracks all document/folder interactions.[vii] Changes such as these require data quality oversight and regular quality checks for monitoring study data.
With continually evolving and increasing industry regulations to manage, the risk of non-compliance and resulting fines increases. Pharmaceutical, medical device, and biotech organizations, as well as their CRO partners, are outsourcing regulatory oversight management to a partner to help ensure their data is up to date.
Supplement and scale expertise through outsourcing to help ensure trial success
Outsourcing has again become an accepted best practice to engage and scale skilled resources for studies and trials as needed to ensure high-quality data for a successful clinical trial program.
Outsourcing expertise is effective for:
- Lack of in-house experience
- Rise in need for specialists within CROs, especially across therapeutic or functional areas such as biostatistics, clinical data management, etc.
- Expanding pipeline of new drug development
- Increasing size, complexity, duration, and cost of clinical trials
- Increase of personalized medicine[viii]
Collaborate with Omega Healthcare Clinical Data Services to meet clinical trial and research goals
Collaborating with Omega Healthcare Clinical Data Services offers a simple but effective model to make data more usable more quickly. To meet the growing demand for high-quality, research-grade RWD, Omega Healthcare enables organizations to scale up a highly skilled, trained, and flexible workforce quickly. Founded by researchers for researchers, the Omega Healthcare team understands the complexity of clinical trial data management and data governance. Omega’s expertise is in RWD services, building databases, and providing research grade records to improve clinical outcomes. Services include curating and unifying a client’s clinical data from disparate sources—all behind the client’s firewall.
[i] “Life Sciences Services Industry Outlook: Winter 2023,” RSM, February 6, 2023
[ii] “Challenges and Opportunities in Clinical Data Management Research Report,” Pharma Intelligence and Oracle. September 2018
[iii] “Clinical Research Trends & Insights for 2023,” WCG
[iv] “Use of Natural Language Processing to Extract Clinical Cancer Phenotypes from Electronic Medical Records,” NIH National Library of Medicine, August 8, 2019
[v] “Challenges and Opportunities in Clinical Data Management Research Report,” Pharma Intelligence and Oracle. September 2018
[vi] Ibid
[vii] “ICH GCP E6 (R2) Compliance in Clinical Trials, Florence Healthcare
[viii] “Clinical Trial Outsourcing Trends and Research,” Thomas Underwood, Quanticate, March 10, 2020